Broadening the Participation of Women and Underrepresented Racial/Ethnic Minorities in STEM: A Mata-Analytic Lens on the Social Cognitive Interest, Choice and PersistenceHypotheses

扩大女性和代表性不足的种族/族裔少数群体对 STEM 的参与：关于社会认知兴趣、选择和持久性假设的 Mata 分析视角

• 批准号: 1252095
• 负责人: Robert Lent
• 金额: $ 29.62万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-08-15 至 2016-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1252095&HistoricalAwards=false
• 关键词: Broadening; Participation; Women; Underrepresented; Racial

There have been numerous calls to expand and diversify the nation's workforce in science, technology, engineering, and mathematics (STEM) fields. In response to these calls, there has been a growing literature on psychological and social variables that might predict and promote engagement in STEM-related educational and career options. Social cognitive career theory (SCCT) has proven to be a useful framework for guiding many studies of STEM engagement and retention, including research focused on women's and underrepresented racial/ethnic minorities' participation in STEM fields. The proposed project will use meta-analytic methods to integrate findings from over 45 individual studies that have tested SCCT's hypotheses in the STEM domain. The findings of this meta-analysis will (a) enhance understanding of theoretical mechanisms that underlie engagement in STEM fields; (b) enable assessment of SCCT's generalizability across gender and race/ethnicity; and (c) provide a robust empirical basis for SCCT-based interventions designed to attract and retain diverse persons within STEM careers. Participating organizations include University of Maryland (primary) and University at Albany, State University of New York (partner). The potential audience for this project includes researchers, practitioners, educators, and policy makers who are interested in broadening the participation of women and underrepresented racial/ethnic minorities in STEM fields. The project will employ a meta-analytic approach to synthesize the findings of individual studies that have been conducted over a period of 32 years (1981 to 2013). The studies to be included in the meta-analysis will be obtained through a comprehensive search of online data bases and a manual search of relevant journals. Both univariate and multivariate (structural equation modeling) statistical techniques will be used to integrate bivariate effect sizes and test SCCT models by gender and race/ethnicity in the context of STEM fields.The meta-analytic findings are intended to provide STEM policy makers, educators, researchers, counselors, and other professionals with a theory-based and empirically-supported understanding of factors that promote the engagement of underrepresented people in STEM fields. This understanding can be used to inform interventions for expanding the diversity of the STEM pipeline. The project will also provide opportunities to train and mentor a diverse group of graduate students and junior faculty members (the team will include women and students of color), fostering their ability to perform theory-driven research and building capacity for future studies on equity in STEM participation. Resources created by the project (e.g., meta-analytic codebooks, a database of SCCT research in STEM fields, correlation matrices) will be made available to other researchers. The research team will disseminate the findings widely to scientific, education, and other communities through such means as conference presentations, journal publications, a project website, and development of evidence-based practice guidelines.

有许多人呼吁扩大和多样化国家在科学，技术，工程和数学（STEM）领域的劳动力。 为了响应这些呼吁，有越来越多的关于心理和社会变量的文献可以预测和促进参与STEM相关的教育和职业选择。 社会认知职业理论（SCCT）已被证明是一个有用的框架，用于指导许多STEM参与和保留的研究，包括研究重点是妇女和代表性不足的种族/少数民族在STEM领域的参与。 拟议的项目将使用荟萃分析方法，整合超过45项独立研究的结果，这些研究已经测试了SCCT在STEM领域的假设。 这项荟萃分析的结果将（a）加强对STEM领域参与的理论机制的理解;（B）能够评估SCCT在性别和种族/民族之间的普遍性;（c）为旨在吸引和留住STEM职业中的多元化人员的SCCT干预措施提供坚实的经验基础。 参与组织包括马里兰州大学（主要）和纽约奥尔巴尼大学州立大学（伙伴）。 该项目的潜在受众包括研究人员，从业人员，教育工作者和政策制定者，他们有兴趣扩大妇女和代表性不足的种族/少数民族在STEM领域的参与。 该项目将采用元分析方法，综合32年（1981年至2013年）期间进行的各项研究的结果。 纳入荟萃分析的研究将通过全面检索在线数据库和手动检索相关期刊获得。 单因素和多因素（结构方程模型）统计技术将用于整合双变量效应量，并在STEM领域的背景下按性别和种族/民族测试SCCT模型。元分析结果旨在为STEM政策制定者，教育工作者，研究人员，顾问，和其他专业人士，以理论为基础，以经验为基础，支持对促进代表性不足的人参与STEM领域的因素的理解。 这种理解可以用来为扩大STEM管道多样性的干预措施提供信息。 该项目还将提供机会，培训和指导研究生和初级教师的多元化群体（该团队将包括女性和有色人种学生），培养他们进行理论驱动研究的能力，并为未来的STEM参与公平研究建立能力。 项目创建的资源（例如，元分析码书，STEM领域SCCT研究数据库，相关矩阵）将提供给其他研究人员。 研究小组将通过会议报告、期刊出版物、项目网站和制定循证实践指南等方式，向科学、教育和其他社区广泛传播研究结果。